Heating Curve Adjustment Using User Feedback for Room Temperature
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Solution Overview
Problem
Optimizing the heating curve of a weather-compensated heat generator in heating systems is complex and typically requires specialist knowledge, making it inaccessible for end-users to adjust efficiently.
Innovation Solution
A method using guided human-machine interaction via a graphical user interface allows users to optimize the heating curve by adjusting the gradient and parallel shift of the heating curve, utilizing a smartphone or internet-enabled device to input feedback and receive optimized parameters, enabling users to set the heating curve without technical expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a heating curve is set to ensure sufficient room temperature, then room comfort is improved, but flow temperature becomes excessively high leading to increased heat losses and heating costs
Solution Approach 1:
The patent implements an iterative optimization process where the control device measures actual room temperatures, compares them to target temperatures, and uses this feedback to adjust heating curve parameters. The system repeatedly queries room temperatures and adjusts the heating curve until the actual temperature matches the target temperature, thereby optimizing the balance between room comfort and energy efficiency.
Solution Approach 2:
The patent optimizes heating curve parameters (gradient and parallel shift) by systematically varying them to achieve the best performance. The control device adjusts these parameters based on measured room temperatures and external conditions, finding the optimal parameter set that minimizes flow temperature while ensuring sufficient room heating, thus reducing heat losses and energy consumption.
2Manufacturing precision
If heating curve optimization is performed using traditional methods, then optimization accuracy is improved, but the process becomes complex and requires specialist knowledge
Solution Approach 1:
The patent enables the heating system to optimize its own heating curve automatically without requiring external specialist intervention. The control device autonomously performs measurements, calculations, and parameter adjustments based on room temperature feedback and external conditions, making the complex optimization process transparent and accessible to end users through a simple graphical interface.
Solution Approach 2:
The patent introduces a graphical user interface as an intermediary between the complex optimization algorithms and the end user. This interface presents simplified interaction options and displays optimization progress in an understandable manner, bridging the gap between sophisticated technical processes and non-expert users.
3Manufacturing precision
If heating curve optimization is performed manually by specialists, then optimization quality is improved, but time consumption and cost increase
Solution Approach 1:
The patent implements a continuous optimization process that operates automatically without interruption. The control device continuously measures room temperatures, evaluates performance against targets, and adjusts heating curve parameters in real-time or near real-time, eliminating the need for lengthy manual specialist interventions and achieving rapid optimization.
Solution Approach 2:
The system uses continuous feedback from room temperature sensors to guide the optimization process. By repeatedly measuring actual temperatures and comparing them to targets, the system quickly converges on optimal parameters, significantly reducing the time required compared to manual methods while maintaining high optimization quality.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enables users to efficiently optimize the heating curve, reducing energy consumption and improving heating system efficiency by allowing users to adjust the heating curve parameters based on real-time feedback, ensuring comfortable room temperatures without requiring specialized knowledge.
Implementation Method 1
the set flow temperature is set depending on the outside temperature
Implementation Method 2
The heat transfer medium can give off the heat to rooms in the building via radiators
Data Source
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AI summary
A method for optimizing the heating curve of a heat generator (10) is provided. The heat generator (10) is part of a heating system (1) with radiators (12), each equipped with thermostatic valves. The heating curve describes the relationship between a flow temperature and an outside temperature using a slope and a parallel shift. A graphical user interface is displayed on a user's terminal device (T) as a human-machine interface for inputting and/or outputting information. The user is instructed to manually open all thermostatic valves. After waiting a defined period, the user provides feedback on whether the actual room temperature in at least one room has reached the setpoint temperature. Depending on the deviation of the actual room temperature from the setpoint temperature, an optimized value for the slope and/or an optimized value for the parallel shift can be determined.The feedback step and the optimization step can be repeated until the actual room temperature in at least one room matches the target room temperature.